EGU23-11812, updated on 04 Aug 2023
EGU General Assembly 2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Implementation and evaluation of Landscape-DNDC model for forestry management methods in a nutrient-rich peatland site in southern Finland.

Ahmed Shahriyer1, Tiina Markkanen1, Henri Kajasilta1, Mika Korkiakoski1, Helena Rautakoski1, Yao Gao1, Suvi Orttenvuouri1, Istem Fer1, Edwin Haas3, David Kraus3, Ruediger Grote3, Mika Aurela1, Annalea Lohila1,2, and Tuula Aalto1
Ahmed Shahriyer et al.
  • 1Finnish Meteorological Institute, Helsinki, Finland
  • 2University of Helsinki, Institute for Atmospheric and Earth System Research
  • 3Karlsruhe Institute of Technology, Institute of Meteorology and Climate Research (IMK-IFU), Germany.

Draining peatlands for forestry and agriculture has been a common practice in Nordic countries in the last century. In drained peatland forests, trees act as carbon sink, while well-aerated peat soil is a source of carbon. Traditionally in even aged forestry all the trees are removed in clear-cut harvesting, whereas the continous cover forestry, with partial removal of a stand in selection cuttings, have been suggested to serve as climate wise option for peatlands.


A process-based model ‘Landscape De-Nitrification De-Composition’ (LDNDC) was used to simulate fluxes of matter and energy of a drained nutrient-rich peatland forest ecosystem in southern Finland. LDNDC utilizes several sub-models for physiology, biogeochemistry, hydrology and microclimate and it simulates ecosystem water, energy and carbon balances including methane balance along with vegetation structure development. Multiple species can be simulated simultaneously as a mixed forest cohort, and contributions of the ground vegetation can be included. Different management methods of the forestry industry, e.g clear cutting or selection cutting have been simulated successfully.


Local meterological data from 2010-2018 was used to drive the model and this data was cycled through several times to start the simulation run from 1969. The amount of carbon storage in the soil was set according to the measurements at nutrient-rich peatlands. Three different simulation runs were made for a clear-cut or a selection cutting taking place in 2016 and a reference forest with no cutting. Pine was simulated as a dominant tree species prior to the management actions along with spruce and birch as a secondary canopy and alpine meadows as ground vegetation. Eddy covariance and chamber measurements from both management and reference sites were used to evaluate model performance.


The model captured the net ecosystem exchange, gross primary production, terrestrial ecosystem respiration and methane fluxes well. The model also captured the changes in soil moisture and water-table level caused by the applied forest management methods. Leaf area index (LAI) of the combined vegetation cohort represented the measured LAI quite well along with the growth of the individual species. Successful implementation of the model resulted in extension of simulations until 2100 using different climate drivers to investigate effects of future management scenarios on various ecosystem balances. These model results can be utilized to provide recommendations for peatland forest management, which can ensure reduction in forestry related emissions and improve the possibilities for the peatland forest to act as a sink of carbon.

How to cite: Shahriyer, A., Markkanen, T., Kajasilta, H., Korkiakoski, M., Rautakoski, H., Gao, Y., Orttenvuouri, S., Fer, I., Haas, E., Kraus, D., Grote, R., Aurela, M., Lohila, A., and Aalto, T.: Implementation and evaluation of Landscape-DNDC model for forestry management methods in a nutrient-rich peatland site in southern Finland., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11812,, 2023.

Supplementary materials

Supplementary material file